Using language models to predict surgical risk using pre-operative clinical notes

Title: Using language models to predict surgical risk using pre-operative clinical notes Description: In this talk, Dr. Chung will explore the use of language models to perform risk stratification using pre-operative clinical notes. Perioperative risk prediction of patients is a challenge surgeons, proceduralists, and anesthesiologists face every day in clinical practice. If a patient is scheduled for a procedure, clinicians must evaluate the medical fitness of the patient and whether they can safely withstand the stress of the procedure. Traditional clinical risk calculators typically only assess a single facet of the patient’s medical comorbidities and typically use structured clinical data such as medical history, laboratory results, etc. to derive a risk prediction. Speaker: Philip Chung, MD, PhD. Postdoctoral Fellow and Clinical Scholar Stanford University Date: April 16, 2024 The University of Washington is committed to ensuring digital accessibility in our services, programs, and activities. If you encounter accessibility barriers using videos found on this channel, please contact UW Video at uwvideo [at] uw [dot] edu.